[Relationship between infant nutrition feeding and childhood obesity in first grade Tehranian students of primary schools, 2009]

Since the prevalence and severity of childhood obesity is increasing, understanding the effective factors for prevention of this disorder is important. A total of 513 students of both sexes in the first year of primary schools, were recruited in this cross-sectional study. They were chosen randomly from 19 regions [of the ministry of education] from Tehran city. Their weight and height were measured, and information on infant birth and feeding characteristics [birth order, birth weight, the type of feeding in infancy, the duration of exclusive breast feeding, the duration of breast feeding and formula feeding] activity levels, the timing of the introduction of complementary foods were obtained. Descriptive statistical methods such as frequency distribution table,%C2 test and central and dispersion parameters were used to describe samples. Eight percent of the children were overweight and 11.7% were obese. There was no significant relation between the type of feeding [breast or formula feeding] and children's BMI. The duration of breast feeding was not significantly associated with children's BMI, Children's BMI had a negative linear association with the duration of exclusive breast feeding [r=-0.151, P=0.0001]. The duration of formula feeding was associated with children's BMI [r=0.108, P=0.007]. Children's BMI had an inverse linear relation with the time of introduction of complementary foods [r=-0.128, P=0.002]. This study shows the importance of duration of breast feeding in reducing the risk of childhood obesity

[Determination of effectvie factors on preeclampsia severity; the application of classification and regression trees]

Despite advances in medical sciences, preeclampsia and eclampsia are still among chief causes of maternal mortality worldwide. In this study, we used classification and regression trees to investigate the role of certain inherent and maternity care factors in severe preeclampsia. This study was done on 1643 pregnant women admitted at 4 hospitals in Iran with one of the 53 maternity complaints were enrolled in this study during 2005. Variables of socioeconomic status, history of pregnancy and diseases, health care visits numbers awareness of warning signs, and the body mass index before pregnancy were recorded in the analysis model as predictors, and preeclampsia severity was entered as the dependent variable. A non-parametric method, known as the classification and regression tree was used to predict the studied consequence. Model validation was done using subsets of the study sample. The results were compared with logistic regression analysis. The incidence of preeclampsia among the studied patients was 5.2%. In model 1, variables of frequent headaches and epigastric pain during pregnancy, the number of previous pregnancies, and the amount of maternal care received were predictive of severe preeclampsia. In model 2, only frequent headaches and the number of previous pregnancies were found predictive. Sensitivity for model 1 and 2 was 47.8% and 39.1%, respectively, and specificity was 96.8% and 93.6%, respectively. In logistic regression analysis, only frequent headache was related to severe preeclampsia [OR=2.5, CI 95%: 1.3-5.0]. This study showed that using of variables that can be measured during maternity care visits to predict severe preeclampsia. Regarding the simple interpretation of tree models and their application in clinical decision making, which can be used in different levels of the health care system